{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Jupyter Notebook version of Menu_stats.py\n", "\n", "(Version 1.0)\n", "\n", "" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### This notebook runs a A/B testing of using static menu versus dynamic menu. \n", "\n", "**Explain the ML project here with a detailed description...**\n", "\n", "> Add here later...\n", "\n", "\n", "**Explain this notebook's results here...**\n", "\n", "> The backtesting case assumes:\n", "\n", "> * Two set of menus: static menu (regular), vs. dynamic menu (adjusted)\n", "> * In both cases customers arrive at the same frequency\n", "> * When customer waiting queue exceeds a thredshold we adjust menus.\n", "> * Customer makes random selection on the menu, the promoted itmes will be ordered with a higher probability.\n", "> * On adjusted menu, we promote items that takes less time to prepare.\n", "> * On regular menu, we promote items that generates most profits.\n", "\n", "> We demonstrate the effect of having a dynamic menu on all of the following metrics:\n", "\n", "> * cumulative profits\n", "> * cumulative waiting time\n", "> * profit per time unit\n", "> * next customer's waiting time\n", "> * number of customer in queue\n", "\n" ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "#!/usr/bin/env python3\n", "# -*- coding: utf-8 -*-\n", "\"\"\"\n", "Created on Mon May 25 13:19:07 2020\n", "@author: root\n", "\"\"\"\n", "# run this command to have pop up animation window in Spyder: %matplotlib qt\n", "%matplotlib inline\n", "\n", "\n", "# import libraries\n", "import numpy as np\n", "import matplotlib.pyplot as plt\n", "import matplotlib.animation as animation\n", "\n", "# ignore warnings\n", "import warnings\n", "warnings.filterwarnings(\"ignore\")\n", "\n", "# set the seed\n", "np.random.seed(42)\n", "import pandas as pd\n", "#import os\n", "#os.chdir('/Users/georgehan/GitHub/menu')\n", "#os.getcwd()" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Set up a simple menu for a salad restaurant:" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " Name Profit_Index Time_Index\n", "0 French Sardines Salad 28 20\n", "1 Lamb Chop Salad 27 19\n", "2 Lobster Salad 26 15\n", "3 Crab Meat Salad 25 15\n", "4 Chicken salad 18 10\n", "5 German fried potatoes Salad 17 8\n", "6 Egg Salad 15 7\n", "7 Organic Green Salad 14 5\n" ] } ], "source": [ "menu = [['French Sardines Salad', 28, 20], \n", " ['Lamb Chop Salad', 27, 19], \n", " ['Lobster Salad', 26, 15],\n", " ['Crab Meat Salad', 25, 15],\n", " ['Chicken salad', 18, 10], \n", " ['German fried potatoes Salad', 17, 8],\n", " ['Egg Salad', 15, 7], \n", " ['Organic Green Salad', 14, 5]\n", " ] \n", "\n", "df = pd.DataFrame(menu, columns = ['Name', 'Profit_Index', 'Time_Index']) \n", "print(df)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Menu regular vs fast:\n", "\n", "Add more description here..." ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "def normalize(df):\n", " profit_scale = max(df['Profit_Index'])\n", " time_scale = max(df['Time_Index'])\n", " df['Profit_Index'] = df['Profit_Index'].astype(float)/profit_scale\n", " df['Time_Index'] = df['Time_Index'].astype(float)/time_scale\n", " return df\n", "\n", "def menu_regular(df):\n", " profits = df['Profit_Index'].tolist()\n", " profits.extend([profits[0], profits[0]])\n", " times = df['Time_Index'].tolist()\n", " times.extend([times[0], times[0]])\n", " return profits, times\n", "\n", "def menu_fast(df):\n", " profits = df['Profit_Index'].tolist()\n", " profits.extend([profits[-1], profits[-1]])\n", " times = df['Time_Index'].tolist()\n", " times.extend([times[-1], times[-1]])\n", " return profits, times\n" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "def menu_simulation(df, N, rate, l, seed=42):\n", " \"\"\"Runs a simulated crowd of customer.\n", " \n", " :param int N : number of discrete steps\n", " :param int T: number of continuous time steps\n", " :param int rate: frequency (minutes) for customer arriving\n", " :feed list of Profit_Indexs and Time_Indexes in df format\n", " :param int seed: initial seed of the random generator\n", " :returns outputs time series: \n", " cumulative profits, cumulative waiting time, profit per time unit\n", " next customer's waiting time, number of customer in queue\n", " \"\"\"\n", " # set the seed\n", " np.random.seed(seed)\n", " \n", " unit_profit = []\n", " profits_output = []\n", " waiting_times_output = []\n", " curr_waiting_times = []\n", " queue_output = []\n", " profits, times = menu_regular(df)\n", " total_profit = 0\n", " total_waiting_time = 0\n", " queue = 0\n", " \n", " for t in range(0, N):\n", " if t%rate == 0:\n", " queue += 1\n", " \n", " if t >= total_waiting_time:\n", " random_dish = np.random.randint(0, 10)\n", " #print(random_dish, end = ' ')\n", " total_profit += profits[random_dish]\n", " total_waiting_time += times[random_dish]\n", " queue -= 1\n", " #print(total_waiting_time, end = ' ')\n", " else:\n", " pass\n", " \n", " profits_output.append(total_profit)\n", " unit_profit.append(total_profit/(t+1))\n", " waiting_times_output.append(total_waiting_time)\n", " curr_waiting_times.append(total_waiting_time-t)\n", " queue_output.append(queue)\n", " \n", " return profits_output, waiting_times_output, unit_profit, curr_waiting_times, queue_output\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Menu simulation: regular vs fast\n", "\n", "\n", "Add more description here..." ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "def menu_simulation_adjusted(df, N, rate, l, seed=42):\n", " \"\"\"Runs a simulated crowd of customer.\n", " \n", " :param int N : number of discrete steps\n", " :param int T: number of continuous time steps\n", " :param int rate: frequency (minutes) for customer arriving\n", " :feed list of Profit_Indexs and Time_Indexes in df format\n", " :param int seed: initial seed of the random generator\n", " :returns outputs time series: \n", " cumulative profits, cumulative waiting time, profit per time unit\n", " next customer's waiting time, number of customer in queue\n", " \"\"\"\n", " # set the seed\n", " np.random.seed(seed)\n", " \n", " unit_profit = []\n", " profits_output = []\n", " waiting_times_output = []\n", " curr_waiting_times = []\n", " queue_output = []\n", " profits, times = menu_regular(df)\n", " total_profit = 0\n", " total_waiting_time = 0\n", " queue = 0\n", " \n", " for t in range(0, N):\n", " if t%rate == 0:\n", " queue += 1\n", " \n", " if t >= total_waiting_time:\n", " random_dish = np.random.randint(0, 10)\n", " #print(random_dish, end = ' ')\n", " total_profit += profits[random_dish]\n", " total_waiting_time += times[random_dish]\n", " queue -= 1\n", " #print(total_waiting_time, end = ' ')\n", " else:\n", " if queue > l:\n", " profits, times = menu_fast(df)\n", " elif queue < l:\n", " profits, times = menu_regular(df)\n", " pass\n", " \n", " profits_output.append(total_profit)\n", " unit_profit.append(total_profit/(t+1))\n", " waiting_times_output.append(total_waiting_time)\n", " curr_waiting_times.append(total_waiting_time-t)\n", " queue_output.append(queue)\n", " \n", " return profits_output, waiting_times_output, unit_profit, curr_waiting_times, queue_output\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Average wait time and Total profit: regular vs fast\n", "\n", "\n", "Add more description here..." ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Average wait time: 13.157894736842104 minutes. \n", "Number of customer served: 76\n", "Total profit: $1679\n" ] } ], "source": [ "seed = 42\n", "N = 1000 # number of discret points\n", "t = np.linspace(0.0, N, N)\n", "P, T, U, C, Q = menu_simulation(df, N, 10, 1.0, seed)\n", "\n", "plt.figure(figsize=(14, 6))\n", "plt.step(t, P, where='mid', lw=1, color='#0492c2')\n", "\n", "plt.figure(figsize=(14, 6))\n", "plt.step(t, Q, where='mid', lw=1, color='#0492c2')\n", "plt.show() \n", "\n", "\n", "print(\"Average wait time: {} minutes. \\nNumber of customer served: {}\".format(N/len(list(set(T))), len(list(set(T)))))\n", "print(\"Total profit: ${}\".format(P[-1]))\n" ] }, { "cell_type": "code", <<<<<<< HEAD "execution_count": 7, ======= "execution_count": 13, >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 "metadata": { "scrolled": true }, "outputs": [ { "data": { "image/png": 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\n", 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Average wait time: 10.75268817204301 minutes. \n", "Number of customer served: 93\n", "Total profit: $1832\n" ] } ], "source": [ "P_adjusted, T_adjusted, U_adjusted, C_adjusted, Q_adjusted = menu_simulation_adjusted(df, N, 10, 2, seed)\n", "\n", "plt.figure(figsize=(14, 6))\n", "plt.step(t, np.array(P_adjusted), where='mid', lw=1, color='#0492c2')\n", "\n", "plt.figure(figsize=(14, 6))\n", "plt.step(t, Q_adjusted, where='mid', lw=1, color='#0492c2')\n", "plt.show() \n", "\n", "\n", "print(\"Average wait time: {} minutes. \\nNumber of customer served: {}\".format(N/len(list(set(T_adjusted))), len(list(set(T_adjusted)))))\n", "print(\"Total profit: ${}\".format(P_adjusted[-1]))" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Static Plot: Profit per time unit comparison\n", "\n", "\n", "Add more description here..." ] }, { "cell_type": "code", <<<<<<< HEAD "execution_count": 8, ======= "execution_count": 21, >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 "metadata": {}, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "W = np.exp(np.array(P)/N) # take log scale of profits for better display of the differences\n", "min_W = np.min(W) # min of W\n", "X = np.exp(np.array(P_adjusted)/N)\n", "max_X = np.max(X)\n", "#X = drifted_brownian_motion(mu, sigma, N, T, seed) # dynamic version\n", "#max_X = np.max(X) # max of X\n", "\n", "\n", "# plot the two Time Series of profits per unit time\n", "\n", "# formatting options\n", "plt.figure(figsize=(14, 6))\n", "plt.title('Static Menu vs. Dynamic Menu', fontsize=24)\n", "plt.xlabel('Time', fontsize=22)\n", "plt.ylabel('Profits in $', fontsize=22)\n", "#plt.xticks(np.linspace(0, N, 2*T + 1), fontsize=18)\n", "plt.yticks(fontsize=18)\n", "\n", "plt.grid(True, which='major', linestyle='--', color='black', alpha=0.6)\n", "plt.step(t, W, where='mid', lw=1, color='#0492c2') # Time Series with static menu\n", "plt.step(t, X, where='mid', lw=1, color='#ff4500') # Time Series with dynamic menu\n", "plt.plot([t[800], t[800]], [W[800], X[800]], 'ko-', lw=2) # vertical black line\n", "plt.plot([t[800], t[800]], [W[800], X[800]], 'ko-', lw=2) # vertical black line\n", "\n", "plt.text(t[800]-100, (W[800] + X[800])/2-1, 'Diff. in ${:.4f}'.format(X[800]-W[800]), fontsize=18) # the text next to the line\n", "plt.show()\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Animation Plot: Profit per time unit comparison\n", "\n", "Can insert GIF here if Animation takes too long to generate\n", "\n", "Add more description here..." ] }, { "cell_type": "code", <<<<<<< HEAD "execution_count": 9, ======= "execution_count": 23, >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "MovieWriter imagemagick unavailable.\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", "\n", "
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\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 " Once \n", " Loop \n", " Reflect \n", "
\n", "
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\n", 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\n", >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.rcParams[\"animation.html\"] = \"jshtml\"\n", "\n", "fig = plt.figure(figsize=(15, 7)) # instantiate a figure\n", "ax = plt.axes(xlim=(0, N), ylim=(min_W, max_X)) # create an axes object\n", "\n", "line_w, = ax.step([], [], where='mid', lw=1, color='#0492c2', alpha=0.8, label='Static Menu') # line for W\n", "line_x, = ax.step([], [], where='mid', lw=1, color='#ff4500', alpha=0.8, label='Dynamic Menu') # line for X\n", "diff_line, = ax.plot([], [], 'ko-', lw=2) # line for the difference\n", "text = ax.text(0, 0, '', fontsize=18)\n", "\n", "# formatting options\n", "ax.set_title('Static Menu vs. Dynamic Menu', fontsize=30)\n", "#ax.set_xticks(np.linspace(0, T, 2*T + 1))\n", "ax.set_xlabel('Time', fontsize=18)\n", "ax.set_ylabel('Unit Profit $', fontsize=18)\n", "ax.tick_params(labelsize=22)\n", "ax.grid(True, which='major', linestyle='--', color='black', alpha=0.6)\n", "ax.legend(loc=2)\n", "\n", "# animation options\n", "frames = 100\n", "factor = N // frames\n", "text_offset = -200\n", "\n", "def animate(i):\n", " upper_bound = (i)*factor # up to what index to take the values\n", " t_i = t[:upper_bound]\n", " \n", " line_w.set_data(list(t_i), list(W[:upper_bound])) # set data for the W line\n", " line_x.set_data(list(t_i), list(X[:upper_bound])) # set data for the X line\n", " diff_line.set_data([t[upper_bound], t[upper_bound]], [W[upper_bound], X[upper_bound]]) # position of the black line\n", " text.set_position((t[upper_bound] + text_offset, (W[upper_bound] + X[upper_bound])/2)) # position of the text\n", <<<<<<< HEAD " text.set_text('Diff. in $\\$ = $ {:.4f}%'.format(np.abs(X[upper_bound] - W[upper_bound])/W[upper_bound])) # diff. value in the text\n", ======= " text.set_text('Diff. in $\\$ = $ {:.2f}%'.format(np.abs(X[upper_bound] - W[upper_bound])/W[upper_bound])) # diff. value in the text\n", >>>>>>> 63e6a56e547f828946e94092cf76fef85d6d49d5 " \n", " return line_w, line_x, diff_line, text,\n", " \n", "# call the animator\t \n", "anim = animation.FuncAnimation(fig, animate, frames=frames, interval=50, blit=True)\n", "# save the animation as GIF file \n", "anim.save('menu_time_series_animation.gif',writer='imagemagick')\n", "\n", "#import matplotlib\n", "#matplotlib.rcParams['animation.embed_limit'] = 2**128\n", "\n", "anim" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" } }, "nbformat": 4, "nbformat_minor": 4 }